The combination of scheduling service appointments and scheduled maintenance presents a problem to any service company. Customers prefer prompt and professional service without undue waiting. This is particularly true of a utility company, such as one providing electricity, gas, telephone, or cable, and the like, which provides on-site service. Everyone wants service, but no one wants to wait for service technicians. Waiting directly impacts the perceived customer service. Utilities must quickly and efficiently respond to ever changing service requests by their customers. Additionally when the service provider schedules a customer request, the provider must determine the time when the service technician will be on-site and provide this information to the customers. Customers' personal schedules are often directly impacted by this time commitment. Additionally, some business customers may alter their business operations based on when the service technician is scheduled to be on site. In such an environment, customer service is directly impacted by the provider's ability to accurately schedule and communicate the time window allocated to the service request.
The service provider, based on experience, must plan the sequence in which the work will be done, and the extent to which resources (workforce members) will be devoted to any particular task. Unforeseen circumstances, such as emergent customer requests and absent employees, may effect this plan with again unforeseen consequences. Such circumstances must be considered by an experienced provider.
One solution involves assigning bands of concentric circles around a central depot that define time windows. A service provider may consider bands of 8-10 AM, 9-11 AM, 10-12 PM and so on. If a customer calls in and their location is calculated to be in one of the bands, then that time window is applied to the customer request. This approach is based on the following assumptions: (1) providers leave from, and return to, a central depot, and (2) service technicians are assumed to all be capable of the same skills. This approach is a simplified heuristic with regard to the general scheduling problem. There may be key aspects of the scheduling problem (such as skills and other constraints) that can be overlooked. There are difficulties in arbitrarily choosing the time window bands and their geographic boundaries.
Similarly, scheduling in the manufacturing or factory setting is of great importance. Customer orders for various items need to be processed in a certain amount of time (i.e., by a shipment date). For each item ordered which is not already in inventory, the item must be manufactured. To manufacture the item, certain resources (materials, machine time, man hours, etc.) used in a predetermined sequence of events are required. In order to efficiently utilize the resources of the manufacturing plant in such manufacturing of items, and ultimately in fulfilling a multiplicity of orders, the manufacturer generally employs a device for scheduling the use of different resources at different dates and times.
Scheduling software is widely used in manufacturing industries to address this problem. The advent of advanced technology in manufacturing systems has highlighted our inability to effectively schedule the production processes. In any production unit, the planner is responsible for making scheduling decisions. Simple scheduling decision rules can effect the system performance to a large extent. Hence, selecting proper scheduling rules is very difficult and such scheduling decisions must often be made in mere seconds.
One of the best approaches to solve these manufacturing scheduling problems has been to use software solutions. Significant manufacturing throughput improvements can be made by using a simulation model to determine a future course for a manufacturing system. Hence, at each scheduling decision point, the scheduling software can be used and a deterministic simulation is run to calculate how control policy impacts the current system.
Scheduling software helps to generate potential scheduling alternatives based on real-time shop information and scheduling knowledge. However, unlike the manufacturing process problem, the order of the service requests to be filled is constantly changing. A manufacturing process itself is fixed and unchanging, while service providers must respond to changing and emergent customer requests.